R Notebook

library(ggplot2)
library(plotly)

# enter in all my data
time_data <- c(15/60,15/60,20/60,10/60,30/60,30/60,
               10/60,5,3.5,7.75,5.5,9.5)
date_data <- c("8/29/2023", "9/7/2023",
               "8/29/2023", "9/3/2023",
               "9/17/2023", "9/24/2023",
               "9/10/2023", "9/24/2023",
               "10/1/2023", "10/8/2023",
               "10/9/2023", "10/10/2023")
duty <- c("starting Github repository",
          "starting Github repository",
          "Selecting Dataset",
          "Selecting Dataset",
          "Describing Dataset",
          "Describing Dataset",
          "Starting R file",
          paste("Making Shiny App",
            "histogram", "word cloud", sep = "\n"),
          paste("Making Shiny App", "line graph"),
          paste("Making Shiny App", "network", 
            sep = "\n"),
          paste("Making Shiny App", "network",
            "map testing", "documentation", 
            sep = "\n"),
          paste("Making Shiny App", "network",
            "extra data", "documentation",
            "video", "time chart",
            sep = "\n"))

# turn date text into a date
# combine all the data into a dataframe
# order by the date
date_data %<>% as.Date(format="%m/%d/%Y")
time_log_data <- data.frame(time_data, date_data, duty)
time_log_data <- time_log_data[order(time_log_data$date_data),]

# plot the data and make the plot fill in green
# change the axis names
# change the tic breaks
#       unfortunately it does not add more date lables :(
p <- ggplot(time_log_data, aes(y=time_data, x=date_data, label = duty))+
  geom_bar(stat = "identity", fill = "lightgreen")+
  xlab("Date")+
  ylab("Hrs Spent") + 
  scale_x_date(date_breaks = "7 day")+
  scale_x_date(date_minor_breaks = "1 day")

Scale for x is already present.
Adding another scale for x, which will replace the existing scale.

# use plotly to add hover information and interactiveness
ggplotly(p)